Enhanced light field depth estimation through occlusion refinement and feature fusion

IF 3.5 2区工程技术 Q2 OPTICS

Optics and Lasers in Engineering Pub Date : 2024-11-04 DOI:10.1016/j.optlaseng.2024.108655

Yuxuan Gao , Haiwei Zhang , Zhihong Chen, Lifang Xue, Yinping Miao, Jiamin Fu

引用次数: 0

Abstract

Light field depth estimation is crucial for various applications, but current algorithms often falter when dealing with complex textures and edges. To address this, we propose a light field depth estimation network based on multi-scale fusion and channel attention (LFMCNet). It incorporates a convolutional multi-scale fusion module to enhance feature extraction and utilizes a channel attention mechanism to refine depth map accuracy. Additionally, LFMCNet integrates the Transformer Feature Fusion Module (TFFM) and Channel Attention-Based Perspective Fusion (CAPF) module for improved occlusion refinement, effectively handling challenges in occluded regions. Testing on the 4D HCI and real-world datasets demonstrates that LFMCNet significantly reduces the Bad Pixel (BP) rate and Mean Square Error (MSE).

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通过遮挡细化和特征融合加强光场深度估算

光场深度估计对各种应用都至关重要，但目前的算法在处理复杂纹理和边缘时往往会出现问题。针对这一问题，我们提出了基于多尺度融合和通道关注的光场深度估计网络（LFMCNet）。它包含一个卷积多尺度融合模块，用于增强特征提取，并利用通道注意机制来提高深度图的准确性。此外，LFMCNet 还集成了变换器特征融合模块（TFFM）和基于通道注意的透视融合模块（CAPF），以改进闭塞细化，从而有效地应对闭塞区域的挑战。在 4D HCI 和真实世界数据集上进行的测试表明，LFMCNet 显著降低了坏像素 (BP) 率和均方误差 (MSE)。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Optics and Lasers in Engineering 工程技术-光学

CiteScore

8.90

自引率

8.70%

发文量

384

审稿时长

42 days

期刊介绍： Optics and Lasers in Engineering aims at providing an international forum for the interchange of information on the development of optical techniques and laser technology in engineering. Emphasis is placed on contributions targeted at the practical use of methods and devices, the development and enhancement of solutions and new theoretical concepts for experimental methods. Optics and Lasers in Engineering reflects the main areas in which optical methods are being used and developed for an engineering environment. Manuscripts should offer clear evidence of novelty and significance. Papers focusing on parameter optimization or computational issues are not suitable. Similarly, papers focussed on an application rather than the optical method fall outside the journal''s scope. The scope of the journal is defined to include the following: -Optical Metrology- Optical Methods for 3D visualization and virtual engineering- Optical Techniques for Microsystems- Imaging, Microscopy and Adaptive Optics- Computational Imaging- Laser methods in manufacturing- Integrated optical and photonic sensors- Optics and Photonics in Life Science- Hyperspectral and spectroscopic methods- Infrared and Terahertz techniques